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Professor Qingjian Zhao currently works at Nanjing Forestry University. In 2008, he graduated from Southeast University of China with a doctorate degree. Worked as a visiting scholar at the University of Toronto from 2015 to 2016. The main research areas include forest ecosystems, ecological economics, value evaluation, agricultural and forestry economic management, forestry industry, carbon accounting, management engineering, etc. Published more than 70 papers and books.
Taihu Lake is the third largest freshwater lake in China. Water ecosystems play an important role in the survival and development of human society. The evaluation of water ecosystem services is helpful to understand and grasp the changing rules of Taihu Lake’s ecosystem services value in recent years. First, we used the Water Environment Qualities Index (WQI) to evaluate the water ecological quality of Taihu Lake; second, on the basis of the survey data from 2010 to 2018, we combined economic and ecological methods to evaluate the water ecosystem of Taihu Lake. The evaluation system includes four major service functions, 11 second-class evaluation indicators and 19 index factor. Research indicates that, (1) in the past 8 years, the WQI of Taihu Lake increased year by year and Taihu Lake changed from moderate pollution to light pollution; (2) provisioning services are the main service of Taihu Lake’s water ecosystem and the order of various service values was provisioning service value > regulation service value > cultural service value > support service value, with water supply as the core function of provisioning services; and (3) the total values in 2010, 2014, and 2018 were 115.39 billion yuan, 113.31 billion yuan, and 119.96 billion yuan, respectively, showing a trend of first decreasing and then increasing. To a certain extent, the improvement in Taihu Lake’s water ecological quality has led to an increase in the value of regulation services.
Qingjian Zhao; Qiuyan Wang. Water Ecosystem Service Quality Evaluation and Value Assessment of Taihu Lake in China. Water 2021, 13, 618 .
AMA StyleQingjian Zhao, Qiuyan Wang. Water Ecosystem Service Quality Evaluation and Value Assessment of Taihu Lake in China. Water. 2021; 13 (5):618.
Chicago/Turabian StyleQingjian Zhao; Qiuyan Wang. 2021. "Water Ecosystem Service Quality Evaluation and Value Assessment of Taihu Lake in China." Water 13, no. 5: 618.
Based on satellite remote sensing image, GIS and Fragstats, this study modeled and calculated the dynamic changes of land use, land cover and landscape patterns in Guizhou Province, China, and calculated the changes of ecosystem service values (ESVs). The impacts of the evolution of landscape patterns on the ESVs were analyzed, and reasonable policy recommendations were made. The findings are as follows: (1) In the past two decades, the area of cropland and grassland has decreased; the area of water bodies, urban and rural, industrial and mining, and residential areas has increased; the area of forestland has increased first and then decreased. (2) The two major types of landscapes, cropland and grassland, are clearly being replaced by two land types, forest land and water bodies. (3) Overall, the degree of landscape aggregation and adjacency has decreased, and the landscape heterogeneity has increased. (4) The total amount of ESV in 2000, 2008, 2013 and 2017 was 2574 × 108 Yuan RMB, 2605 × 108 Yuan RMB, 2618 × 108 Yuan RMB and 2612 × 108 Yuan RMB, respectively. The changes of landscape patterns had important impacts on the ESVs. In order to solve the problems caused by the increasingly prominent changes in the landscape patterns and improve the ESVs, it is necessary to rationally plan and allocate land resources, optimize the industrial structures, and develop effective regulatory policies.
Qingjian Zhao; Zuomin Wen; Shulin Chen; Sheng Ding; Minxin Zhang. Quantifying Land Use/Land Cover and Landscape Pattern Changes and Impacts on Ecosystem Services. International Journal of Environmental Research and Public Health 2019, 17, 126 .
AMA StyleQingjian Zhao, Zuomin Wen, Shulin Chen, Sheng Ding, Minxin Zhang. Quantifying Land Use/Land Cover and Landscape Pattern Changes and Impacts on Ecosystem Services. International Journal of Environmental Research and Public Health. 2019; 17 (1):126.
Chicago/Turabian StyleQingjian Zhao; Zuomin Wen; Shulin Chen; Sheng Ding; Minxin Zhang. 2019. "Quantifying Land Use/Land Cover and Landscape Pattern Changes and Impacts on Ecosystem Services." International Journal of Environmental Research and Public Health 17, no. 1: 126.
In the context of global climate change, energy conservation and greenhouse effect gases (GHG) reduction are major challenges to mankind. The forestry-pulp and paper industry is a typical high energy consumption and high emission industry. We conducted in-depth research on the energy flows and carbon footprint of the forestry-pulp paper industry. The results show that: (1) The main sources of energy supply include external fossil fuel coal and internal biomass fuel black liquor, which supply 30,057,300 GJ and 14,854,000 GJ respectively; in addition, the energy produced by diesel in material transportation reaches 11,624,256 GJ. (2) The main energy consumption processes include auxiliary engineering projects, material transportation, papermaking, alkali recovery, pulping and other production workshops. The percentages of energy consumption account for 26%, 18%, 15%, 10% and 6%, respectively. (3) The main sources of carbon include coal and forest biomass, reaching 770,000 tons and 1.39 million tons, respectively. (4) Carbon emissions mainly occur in fuel combustion in combined heating and power (CHP) and diesel combustion in material transportation, reaching 6.78 million tons and 790,000 tons of carbon, respectively. (5) Based on steam and electricity consumption, the indirect carbon emissions of various thermal and electric energy production units were calculated, and the key energy consumption process units and hotspot carbon flow paths were further found. This research established a theoretical and methodological basis for energy conservation and emission reduction.
Qingjian Zhao; Sheng Ding; Zuomin Wen; Anne Toppinen. Energy Flows and Carbon Footprint in the Forestry-Pulp and Paper Industry. Forests 2019, 10, 725 .
AMA StyleQingjian Zhao, Sheng Ding, Zuomin Wen, Anne Toppinen. Energy Flows and Carbon Footprint in the Forestry-Pulp and Paper Industry. Forests. 2019; 10 (9):725.
Chicago/Turabian StyleQingjian Zhao; Sheng Ding; Zuomin Wen; Anne Toppinen. 2019. "Energy Flows and Carbon Footprint in the Forestry-Pulp and Paper Industry." Forests 10, no. 9: 725.
Forest fire prevention is important because of human communities near forests or in the wildland-urban interfaces. Short-term forest fire danger rating prediction is an effective way to provide early guidance for forest fire managers. It can therefore effectively protect the forest resources and enhance the sustainability of the forest ecosystem. However, relevant existing forest fire danger rating prediction models operate well only when applied to distinct climates and fuel types separately. There are desires for an effective methodology, which can construct a specific short-term prediction model according to an evaluation of the data from that specific region. Moreover, a suitable method for prediction model construction needs to deal with some big data related computing challenges (i.e., data diversity coupled with complexity of solution space, and the requirement of real-time forest fire prevention application) when massively observed heterogeneous parameters are available for prediction (e.g., meteorology factor, the amount of litter in the area, soil moisture, etc.). To capture the influences of multiple prediction factors on the prediction results and effectively learn from fast cumulative historical big data, artificial intelligence methods are investigated in this paper, yielding a short-term Ratings of Forest Fire Danger Prediction via Multiclass Logistic Regression (or RAFFIA) model for forest fire danger rating online prediction. Experimental evaluations conducted on a sensor-based forest fire prevention experimental station show that RAFFIA (with 98.71% precision and 0.081 root mean square error) is more effective than the Least Square Fitting Regression (LSFR) and Random Forests (RF) prediction models.
Lei Wang; Qingjian Zhao; Zuomin Wen; Jiaming Qu. RAFFIA: Short-term Forest Fire Danger Rating Prediction via Multiclass Logistic Regression. Sustainability 2018, 10, 4620 .
AMA StyleLei Wang, Qingjian Zhao, Zuomin Wen, Jiaming Qu. RAFFIA: Short-term Forest Fire Danger Rating Prediction via Multiclass Logistic Regression. Sustainability. 2018; 10 (12):4620.
Chicago/Turabian StyleLei Wang; Qingjian Zhao; Zuomin Wen; Jiaming Qu. 2018. "RAFFIA: Short-term Forest Fire Danger Rating Prediction via Multiclass Logistic Regression." Sustainability 10, no. 12: 4620.
From the perspective of supply chain, benchmarking the embodied carbon flows and emissions landscape is to study the carbon footprint in supply chain production and process management. On the basis of the theory of a green supply chain, this paper conducted its research through the following steps. First, a multi-level supply chain model was proposed and established, and various sectors, production and management processes, and inputs and outputs of different resources were integrated into the supply chain network, and then divided into multiple levels. Second, a multi-level embodied carbon flow and emissions model was established through the Leontief Inverse. Third, based on the operation data of forestry-pulp and paper companies, the embodied carbon flows and emissions at all levels and sectors were estimated and analyzed. Finally, the dismantling and processing methods of complex carbon network structures were explored, the hot-spot carbon sources and paths were obtained, and the low-carbon innovation and development strategies were proposed. The research results show that: (1) Supply chain is a new idea and carrier to study the spatial and state changes of carbon, and also provides a platform for spatial landscape analysis of carbon; (2) The modeling and calculation of carbon flows and emissions offer a new solution of evaluating the environmental performance of companies with high pollution and emission such as forestry-pulp and paper companies, and provide the government effective technical support to implement environmental regulations and formulate carbon emission reduction policies.
Qingjian Zhao; Zuomin Wen; Anne Toppinen. Constructing the Embodied Carbon Flows and Emissions Landscape from the Perspective of Supply Chain. Sustainability 2018, 10, 3865 .
AMA StyleQingjian Zhao, Zuomin Wen, Anne Toppinen. Constructing the Embodied Carbon Flows and Emissions Landscape from the Perspective of Supply Chain. Sustainability. 2018; 10 (11):3865.
Chicago/Turabian StyleQingjian Zhao; Zuomin Wen; Anne Toppinen. 2018. "Constructing the Embodied Carbon Flows and Emissions Landscape from the Perspective of Supply Chain." Sustainability 10, no. 11: 3865.
The Laoshan forest is the largest forest in Nanjing, and it plays an important role in water resource management in Nanjing. The objectives of this study are to determine if the temperature vegetation dryness index (TVDI) is suitable to estimate the soil moisture and if soil moisture is significantly affected by tree species in the Laoshan forest. This paper calculated the spatial distribution of TVDI using LANDSAT-5 TM data. Sixty-two observation points of in situ soil moisture measurements were selected to validate the effectiveness of the TVDI as an index for assessing soil moisture in the Laoshan forest. With the aid of the three different temporal patterns, which are 10 January 2011, 18 May 2011 and 23 September 2011, this paper used the TVDI to investigate the differences of soil moisture under four kinds of mono-species forests and two kinds of mixed forests. The results showed that there is a strong and significant negative correlation between the TVDI and the in situ measured soil moisture (R2 = 0.15–0.8, SE = 0.015–0.041 cm3/cm3). This means that the TVDI can reflect the soil moisture status under different tree species in the Laoshan forest. The soil moisture under these six types of land cover from low to high is listed in the following order: Eucommia ulmoides, Quercus acutissima, broadleaf mixed forest, Cunninghamia lanceolata, coniferous and broadleaf mixed forest and Pinus massoniana.
Shulin Chen; Zuomin Wen; Hong Jiang; Qingjian Zhao; Xiuying Zhang; Yan Chen. Temperature Vegetation Dryness Index Estimation of Soil Moisture under Different Tree Species. Sustainability 2015, 7, 11401 -11417.
AMA StyleShulin Chen, Zuomin Wen, Hong Jiang, Qingjian Zhao, Xiuying Zhang, Yan Chen. Temperature Vegetation Dryness Index Estimation of Soil Moisture under Different Tree Species. Sustainability. 2015; 7 (9):11401-11417.
Chicago/Turabian StyleShulin Chen; Zuomin Wen; Hong Jiang; Qingjian Zhao; Xiuying Zhang; Yan Chen. 2015. "Temperature Vegetation Dryness Index Estimation of Soil Moisture under Different Tree Species." Sustainability 7, no. 9: 11401-11417.